Dynamics of Adjusted Net National Income Per Capita and Its Determinants: Application of ARDL and Vector Error Correction Models to Sub-Saharan Africa

Abstract

Over the past few decades, the Sub-Saharan Africa (SSA) region has experienced a myriad of economic challenges, including highly dynamic trade trends, fluctuating commodity prices, stagnating capital accumulation trends, varying levels of foreign investment, and rapid population growth. These, coupled with the region's unique socio-economic landscape, necessitate a comprehensive understanding of how different variables interact to shape income outcomes. This paper employs the Autoregressive Distributed Lag (ARDL) and Vector Correction Models (VECM) to analyse the dynamics of Adjusted Net National Income Per Capita (ANNIPC). The results show complex interdependencies of capital formation, trade, inflation, and demographics indicating that increased gross capital formation and manageable inflation positively affect ANNIPC. This underscores the need for policymakers in SSA to prioritise capital investment strategies, such as infrastructure development and enhanced financial access, to spur sustainable economic growth. Additionally, improving export capacities and trade balances for elevating income levels and paying attention to population dynamics is essential. Similarly, integrating human capital enhancement through education and skills training into economic policies remains one of the important focal areas. We also found a quick adjustment to long-run equilibrium among variables that underscores the need for proactive policymaking to mitigate short-term economic shocks. A comprehensive approach, considering these interconnected factors, will be critical for SSA's governments to create a stable economic environment, ultimately fostering resilience and prosperity in the region.